Human capital routines and sustainability trade-offs
Bibliographic record
Abstract
Purpose Sustainable operations management is characterized by environmental, social and operational goals. The implementation of routines to protect and direct the effective use of human capital is proposed to potentially improve all three dimensions. However, functional managers with overlapping responsibilities at the plant-level might implement human capital routines based on their individual functional schemas. The purpose of this paper is to investigate whether functional managers have conflicting perceptions of human capital routines, due to narrow perceptions benefiting their own functional domain, and thus generate trade-offs. Design/methodology/approach A combination of matched survey and archival data from 198 manufacturing plants is used to explore the degree to which functional managers have conflicting perceptions of human capital routines and the effects of these perceptions on sustainability outcomes. Findings The results indicate that on average functional managers have conflicting perceptions that generate trade-offs between sustainability dimensions. However, when functional managers had a shared perception better outcomes on all sustainability dimensions are shown. Thus, human capital routines can be a powerful tool for sustainability only if senior management can promote a shared schema across functional managers. Originality/value Differently than most previous studies assuming shared sustainability goals within an organization, this study considers a multiplicity of functional actors with potentially varying perceptions about sustainability goals and links these to organizational routine implementation and outcomes. Additionally, the dynamic and subjective nature of organizational routines, such as human capital routines, is proposed to explain contradictory impacts in a multi-objective setting such as sustainable operations management.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".